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Dataset Title:  Amino acid enantiomeric ratios (D/L) of high and low molecular weight (HMW,
LMW) DOM collected from the North Pacific Subtropical Gyre and Central North
Atlantic
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Institution:  BCO-DMO   (Dataset ID: bcodmo_dataset_811458)
Range: depth = 7.5 to 2500.0m
Information:  Summary ? | License ? | ISO 19115 | Metadata | Background (external link) | Subset | Data Access Form | Files
 
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The Dataset Attribute Structure (.das) for this Dataset

Attributes {
 s {
  location {
    String bcodmo_name "site";
    String description "Sample collection location. HOT = Hawaii Ocean Time Series station ALOHA (22° 45'N, 158° 00'W) in North Pacific Subtropical Gyre (NPSG); BATS = Hawaii Ocean Time Series station ALOHA (22° 45'N, 158° 00'W) in North Pacific Subtropical Gyre (NPSG)";
    String long_name "Location";
    String units "unitless";
  }
  year {
    Int16 _FillValue 32767;
    Int16 actual_range 2014, 2015;
    String bcodmo_name "year";
    String description "Year of sample collection; format: YYYY";
    String long_name "Year";
    String nerc_identifier "https://vocab.nerc.ac.uk/collection/P01/current/YEARXXXX/";
    String units "unitless";
  }
  season {
    String bcodmo_name "season";
    String description "Season of sample collection";
    String long_name "Season";
    String units "unitless";
  }
  sample_type {
    String bcodmo_name "sample_type";
    String description "DOM Fraction";
    String long_name "Sample Type";
    String units "unitless";
  }
  depth {
    String _CoordinateAxisType "Height";
    String _CoordinateZisPositive "down";
    Float64 _FillValue NaN;
    Float64 actual_range 7.5, 2500.0;
    String axis "Z";
    String bcodmo_name "depth";
    Float64 colorBarMaximum 8000.0;
    Float64 colorBarMinimum -8000.0;
    String colorBarPalette "TopographyDepth";
    String description "Sample depth";
    String ioos_category "Location";
    String long_name "Depth";
    String nerc_identifier "https://vocab.nerc.ac.uk/collection/P09/current/DEPH/";
    String positive "down";
    String standard_name "depth";
    String units "m";
  }
  amino_acid {
    String bcodmo_name "amino_acid";
    String description "Amino acid";
    String long_name "Amino Acid";
    String units "unitless";
  }
  Mol_pcnt {
    Float32 _FillValue NaN;
    Float32 actual_range 1.6, 38.6;
    String bcodmo_name "amino_conc";
    String description "Relative amino acid molar abundance";
    String long_name "Mol Pcnt";
    String units "unitless (percent)";
  }
  Mol_pcnt_stdev {
    Float32 _FillValue NaN;
    Float32 actual_range 0.2, 3.9;
    String bcodmo_name "amino_conc";
    String description "Standard deviation of Mol_pcnt";
    String long_name "Mol Pcnt Stdev";
    String units "unitless (percent)";
  }
  pcnt_D {
    Float32 _FillValue NaN;
    Float32 actual_range 1.3, 44.3;
    String bcodmo_name "amino_conc";
    String description "Relative amount of D-amino acid enantiomer";
    String long_name "PCNT D";
    String units "unitless (percent)";
  }
  pcnt_D_stdev {
    Float32 _FillValue NaN;
    Float32 actual_range 0.3, 1.4;
    String bcodmo_name "amino_conc";
    String description "Standard deviation of pcnt_D";
    String long_name "Pcnt D Stdev";
    String units "unitless (percent)";
  }
  D_L_ratio {
    Float32 _FillValue NaN;
    Float32 actual_range 0.01, 0.79;
    String bcodmo_name "amino_conc";
    String description "Ratio of D-AA to L-AA abundance";
    String long_name "D L Ratio";
    String units "unitless";
  }
  D_L_ratio_stdev {
    Float32 _FillValue NaN;
    Float32 actual_range 0.003, 0.014;
    String bcodmo_name "amino_conc";
    String description "Standard deviation of D_L_ratio";
    String long_name "D L Ratio Stdev";
    String units "unitless";
  }
 }
  NC_GLOBAL {
    String access_formats ".htmlTable,.csv,.json,.mat,.nc,.tsv";
    String acquisition_description 
"Sample Collection  
 Samples were collected on two separate research cruises aboard the R/V Kilo
Moana in August 2014 and May 2015. Sampling was conducted at the Hawaii Ocean
Time Series Station ALOHA (A Long-Term Oligotrophic Habitat Assessment;
22\\u00b0 45'N, 158\\u00b0 00'W) and the Bermuda Atlantic Time Series Site
(BATS; 31\\u00b0 40'N, 64\\u00b0 10'W) in the Central North Atlantic.
 
Surface water was sampled via the vessel's underway sampling system. The
intake pipe is situated on the forward starboard hull section of the vessel
approximately 7.5 m below the waterline. The laboratory seawater tap was
allowed to flush for 2 hours prior to each sampling. Seawater was pre-filtered
through 53 \\u00b5m Nitex mesh, and pumped through a 0.2 \\u00b5m
polyethersulfone (PES) cartridge filter (Shelco Filters, Micro Vantage, water
grade, 9.75\\\" DOE, polycarbonate housing) prior to introduction to the
ultrafiltration system. Large volume subsurface water samples were collected
using successive casts of a rosette equipped with 24 x 12 L Niskin bottles.
 
Tangential-Flow Ultrafiltration  
 The main UF system was constructed using a modified design of the system
described in Roland et al. (2009), and expanded on by Walker et al. (2011).
Briefly, the system was comprised of four-spiral wound PES UF membranes,
having a nominal molecular weight cut off of 2.5 kD (GE Osmonics GH2540F30,
40-inch long, 2.5-inch diameter). The membranes were mounted in stainless
steel housings, plumbed in parallel to a 100 L fluorinated HDPE reservoir,
with flow driven by a 1.5 HP stainless steel centrifugal pump (Goulds Pumps,
Stainless steel centrifugal pump, NPE series 1 x 1-1/4 -6, close coupled to a
1-1/2 horsepower, 3500 RPM, 60 Hz, 3 phase, Open Drip Proof Motor; 5.75 Inch
Impeller Diameter, Standard Viton Mechanical Seals). All other system plumbing
components contacting seawater were composed of polytetrafluoroethylene (PTFE)
or stainless steel.
 
The system was run continuously at a membrane pressure of 40-50 psi, resulting
in permeation flow rates of 1-2 L/min, depending primarily on the temperature
of the feed seawater. Sample water was fed into the system using peristaltic
pumps and platinum cured silicone tubing at a flow rate matched to the system
permeation rates to ensure a constant system volume of approximately 100 L.
 
Seawater samples of 3000-4000 L were concentrated to a final retentate volume
of 15-20 L, drained from the system into acid washed PC carboys and
refrigerated (less than 12 hours at 2C) until the next phase of processing.
Samples requiring storage for longer than 12 hours were frozen and stored at
-20\\u00b0C. The UF system was then reconfigured to a smaller volume system,
consisting of a single membrane having a smaller nominal molecular weight
cutoff (GE Osmonics GE2540F30, 40-inch long, 2.5-inch diameter, 1 kD MWCO),
and a 2.5 L PES reservoir for further volume reduction and subsequent salt
removal (diafiltration). Using this smaller system, samples were reduced to
2-3 L under lower pressure (25 psi, permeation rate = 250 mL/min). Samples
were then diafiltered using 40 L of 18.2 M\\u03a9 Milli-Q (ultrapure) water,
adding water to the sample retentate reservoir at the same rate of membrane
permeation. Reduced and diafiltered samples were stored in acid washed PC
bottles at -20\\u00b0C for transport. In the laboratory, samples were further
concentrated by rotary evaporation using pre-combusted glassware (450 \\u00b0C,
5 h). A molecular sieve and a liquid nitrogen trap were placed between the
vacuum pump and rotovap chamber to ensure no contamination of isolated
material by back streaming of hydrocarbons or other contaminants. After
reduction to 50-100 mL, samples were dried to powder via centrifugal
evaporation in PTFE centrifuge tubes. Dry material was homogenized with an
ethanol cleaned agate mortar and pestle, transferred to pre-combusted glass
vials, and stored in a desiccation cabinet until subsequent analyses.
 
Solid Phase Extraction  
 Solid phase extraction was conducted using PPL sorbent (Agilent Bondesil
PPL, 125 \\u00b5m particle size, part # 5982-0026) following the general
recommendations of Dittmar et al. (2008) and Green et al. (2014), including
loading rates, seawater to sorbent ratios, and elution volumes and rates.
Between 300 and 500 g of sorbent was used for each extraction, depending on
sample volume and DOC concentration, with average loading of 4.2 \\u00b1 1.5 L
UF permeate per g sorbent representing 1.9 \\u00b1 0.6 mg DOC per g sorbent or
a DOC to sorbent mass ratio of 1:600 \\u00b1 200. This is in line with both the
recommendations of Dittmar et al. (2008) (maximum loading = 10 L seawater per
g sorbent) and Li et al. (2016) (DOC to sorbent ratio = 1:800). Permeate from
the UF system was fed through PTFE tubing to a pair of 200 L HDPE barrels. The
permeate water was then acidified in 200 L batches to pH 2 by adding 400 mL of
6 M HCl (Fisher Chemical, ACS Plus grade). Batch samples were mixed
continuously during collection, acidification, and loading using a peristaltic
pump and platinum cured Si and PTFE tubing positioned at the surface and
bottom of each barrel. Acidified batches of seawater permeate were then pumped
through the SPE sorbent. SPE flow rates were matched to UF permeation rates
(1-2 L/min), such that a pair of 200 L barrels allowed one barrel to be filled
while the contents of the other was passed through the sorbent.
 
Three custom SPE column configurations were used to contain the sorbent
material. The column configuration was modified several times for ease of use
on subsequent cruises. First, an open, gravity fed, large (49 mm ID x 1000 mm
length, 1875 mL volume) glass chromatography column with 40 \\u00b5m fritted
disk and PTFE stopcock (Kimble-Chase, Kontes) was used. Next, we tested a
custom built high-pressure SS housing (10 cm ID x 3.5 cm bed height), and
finally a parallel combination of 2 medium-pressure glass chromatography
columns (Kimble-Chase, Kontes, Chromaflex LC, 4.8 mm ID x 30 cm, 543 mL
volume). While all designs proved to be functionally equivalent, the latter
parallel combination of 2 medium-pressure glass columns ultimately provided
the best configuration in order to maximize flow rates while simultaneously
optimizing the ratio of sorbent bed height to loading speed. Further, the
commercial availability and ease of use associated with this configuration
made it our preferred design.
 
Following sample loading, the SPE sorbent was desalted with 6 L of pH 2
ultrapure water at a low flow rate (250-300 mL/min). After desalting, the SPE
sorbent was transferred to a glass chromatography column (75 mm ID x 300 mm
length, 40 \\u00b5m fritted disk, PTFE stopcock) with ultrapure water rinses to
ensure quantitative transfer. Isolated organic material was then eluted from
the sorbent with five to six 500 mL additions of methanol. The eluted methanol
solution was stored in pre-combusted amber glass bottles at -20\\u00b0C for
transport. Similar to UF samples, the methanol-eluted solutions were first
reduced by rotary evaporation to 50-100 mL. Samples were then dried to powder
via centrifugal evaporation in PTFE centrifuge tubes. Dry material was
homogenized with an ethanol cleaned agate mortar and pestle, transferred to
pre-combusted glass vials, and stored in a desiccation cabinet until elemental
and isotopic analyses.
 
Amino Acid Enantiomeric Analysis  
 AA enantiomers were analyzed by gas chromatography-mass spectrometry (GC-MS;
Agilent 7890A + 5975B) using a chiral column (Altech Chirasi-L-Val, 50 m
length, 0.25 mm internal diameter, 0.16 \\u03bcm film thickness). 1 \\u03bcL of
sample was injected through a splitless inlet at 200\\u00b0C, using helium
carrier (0.9 mL/min). Individual amino acids were separated using a 4-ramp,
57.5 min temperature program: 45\\u00b0C start;\\u00a0 2\\u00b0C/min to
75\\u00b0C;\\u00a0 4\\u00b0C/min to 110\\u00b0C;\\u00a0 1\\u00b0C/min to
125\\u00b0C;\\u00a0 4\\u00b0C/min to a final temperature of 200\\u00b0C.
Quantification was based on retention times for authentic D and L standards of
each AA, coupled with ion peak areas obtained using single-ion monitoring,
based on the following characteristic ion fragments (m/z): Alanine (Ala), 140;
valine (Val), 168.1; threonine (Thr), 153; glycine (Gly), 126; isoleucine and
leucine (Ile and Leu), 182.1; serine (Ser), 138; proline (Pro), 166.1;
aspartic acid (Asp), 184; glutamic acid (Glu), 180; and phenylalanine (Phe),
190.1. Total amino acid yields, and relative abundance were quantified using
mixed L-AA standards in a linear four-point calibration curve ranging from
1-1000 \\u03bcmol/AA. For each AA, peak areas for both enantiomers were
converted to molar quantities using the calibration curve for the
corresponding ion fragment. Molar percentage abundance (Mol%) for each AA
measured was calculated using the sum of the D and L enantiomers.";
    String awards_0_award_nid "701743";
    String awards_0_award_number "OCE-1358041";
    String awards_0_data_url "http://www.nsf.gov/awardsearch/showAward.do?AwardNumber=1358041";
    String awards_0_funder_name "NSF Division of Ocean Sciences";
    String awards_0_funding_acronym "NSF OCE";
    String awards_0_funding_source_nid "355";
    String awards_0_program_manager "Henrietta N Edmonds";
    String awards_0_program_manager_nid "51517";
    String cdm_data_type "Other";
    String comment 
"Amino Acid Enantiomeric Ratios (D/L) 
  PI: Matthew McCarthy (UC Santa Cruz) 
  Co-PI: Thomas Guilderson (UC Santa Cruz) 
  Version date: 13 May 2020";
    String Conventions "COARDS, CF-1.6, ACDD-1.3";
    String creator_email "info@bco-dmo.org";
    String creator_name "BCO-DMO";
    String creator_type "institution";
    String creator_url "https://www.bco-dmo.org/";
    String data_source "extract_data_as_tsv version 2.3  19 Dec 2019";
    String dataset_current_state "Final and no updates";
    String date_created "2020-05-13T19:42:12Z";
    String date_modified "2020-05-20T15:39:28Z";
    String defaultDataQuery "&time<now";
    String doi "10.26008/1912/bco-dmo.811458.1";
    Float64 geospatial_vertical_max 2500.0;
    Float64 geospatial_vertical_min 7.5;
    String geospatial_vertical_positive "down";
    String geospatial_vertical_units "m";
    String history 
"2020-08-03T17:17:39Z (local files)
2020-08-03T17:17:39Z https://erddap.bco-dmo.org/tabledap/bcodmo_dataset_811458.das";
    String infoUrl "https://www.bco-dmo.org/dataset/811458";
    String institution "BCO-DMO";
    String instruments_0_acronym "Niskin bottle";
    String instruments_0_dataset_instrument_nid "811469";
    String instruments_0_description "A Niskin bottle (a next generation water sampler based on the Nansen bottle) is a cylindrical, non-metallic water collection device with stoppers at both ends. The bottles can be attached individually on a hydrowire or deployed in 12, 24, or 36 bottle Rosette systems mounted on a frame and combined with a CTD. Niskin bottles are used to collect discrete water samples for a range of measurements including pigments, nutrients, plankton, etc.";
    String instruments_0_instrument_external_identifier "https://vocab.nerc.ac.uk/collection/L22/current/TOOL0412/";
    String instruments_0_instrument_name "Niskin bottle";
    String instruments_0_instrument_nid "413";
    String instruments_0_supplied_name "rosette equipped with 24 x 12 L Niskin bottles";
    String instruments_1_acronym "Pump-Ship Intake";
    String instruments_1_dataset_instrument_nid "811468";
    String instruments_1_description "The 'Pump-underway ship intake' system indicates that samples are from the ship's clean water intake pump. This is essentially a surface water sample from a source of uncontaminated near-surface (commonly 3 to 7 m) seawater that can be pumped continuously to shipboard laboratories on research vessels. There is typically a temperature sensor near the intake (known as the hull temperature) to provide measurements that are as close as possible to the ambient water temperature. The flow from the supply is typically directed through continuously logged sensors such as a thermosalinograph and a fluorometer. Water samples are often collected from the underway supply that may also be referred to as the non-toxic supply. Ideally the data contributor has specified the depth in the ship's hull at which the pump is mounted.";
    String instruments_1_instrument_external_identifier "https://vocab.nerc.ac.uk/collection/L05/current/31/";
    String instruments_1_instrument_name "Pump - Surface Underway Ship Intake";
    String instruments_1_instrument_nid "534";
    String instruments_1_supplied_name "underway sampling system";
    String instruments_2_acronym "Gas Chromatograph";
    String instruments_2_dataset_instrument_nid "811475";
    String instruments_2_description "Instrument separating gases, volatile substances, or substances dissolved in a volatile solvent by transporting an inert gas through a column packed with a sorbent to a detector for assay. (from SeaDataNet, BODC)";
    String instruments_2_instrument_external_identifier "https://vocab.nerc.ac.uk/collection/L05/current/LAB02/";
    String instruments_2_instrument_name "Gas Chromatograph";
    String instruments_2_instrument_nid "661";
    String instruments_2_supplied_name "GC-MS; Agilent 7890A + 5975B";
    String instruments_3_acronym "Mass Spec";
    String instruments_3_dataset_instrument_nid "811476";
    String instruments_3_description "General term for instruments used to measure the mass-to-charge ratio of ions; generally used to find the composition of a sample by generating a mass spectrum representing the masses of sample components.";
    String instruments_3_instrument_external_identifier "https://vocab.nerc.ac.uk/collection/L05/current/LAB16/";
    String instruments_3_instrument_name "Mass Spectrometer";
    String instruments_3_instrument_nid "685";
    String instruments_3_supplied_name "GC-MS; Agilent 7890A + 5975B";
    String keywords "acid, amino, amino_acid, bco, bco-dmo, biological, chemical, D_L_ratio, D_L_ratio_stdev, data, dataset, depth, deviation, dmo, erddap, management, mol, Mol_pcnt, Mol_pcnt_stdev, oceanography, office, pcnt, pcnt_D, pcnt_D_stdev, preliminary, ratio, sample, sample_type, season, standard, standard deviation, stdev, type, year";
    String license "https://www.bco-dmo.org/dataset/811458/license";
    String metadata_source "https://www.bco-dmo.org/api/dataset/811458";
    String param_mapping "{'811458': {'depth': 'flag - depth'}}";
    String parameter_source "https://www.bco-dmo.org/mapserver/dataset/811458/parameters";
    String people_0_affiliation "University of California-Santa Cruz";
    String people_0_affiliation_acronym "UC Santa Cruz";
    String people_0_person_name "Matthew D. McCarthy";
    String people_0_person_nid "557245";
    String people_0_role "Principal Investigator";
    String people_0_role_type "originator";
    String people_1_affiliation "University of California-Santa Cruz";
    String people_1_affiliation_acronym "UC Santa Cruz";
    String people_1_person_name "Thomas Guilderson";
    String people_1_person_nid "51494";
    String people_1_role "Co-Principal Investigator";
    String people_1_role_type "originator";
    String people_2_affiliation "Woods Hole Oceanographic Institution";
    String people_2_affiliation_acronym "WHOI BCO-DMO";
    String people_2_person_name "Shannon Rauch";
    String people_2_person_nid "51498";
    String people_2_role "BCO-DMO Data Manager";
    String people_2_role_type "related";
    String project "DON Microbial Nitrogen Pump";
    String projects_0_acronym "DON Microbial Nitrogen Pump";
    String projects_0_description 
"Dissolved organic nitrogen is one of the most important - but perhaps least understood - components of the modern ocean nitrogen cycle. While dissolved organic nitrogen represents a main active reservoir of fixed and seemingly biologically-available nitrogen, at the same time most of ocean's dissolved organic nitrogen pool is also apparently unavailable for use by organisms. Recently, the idea of the \"Microbial Carbon Pump\" has emerged, providing a renewed focus on microbes as primary agents for the formation of biologically-available dissolved material. However, the role that microbes play in transformation of biologically-available dissolved organic nitrogen is still lacking. In order to fill gaps in this knowledge, researchers from the University of California Santa Cruz will apply a series of new analytical approaches to test the role of microbial source and transformation in formation of the ocean's biologically-available dissolved organic nitrogen pool. Results from this study will address one of the major unknowns of both chemical oceanography and the ocean nitrogen cycle.
Broader Impacts:
This proposal will provide oceanographers new tools to test ideas of microbial organic matter sequestration in a world where the oceans are rapidly changing. High school, undergraduate, graduate and post-doctoral education will be furthered through active participation in lab, field, and data synthesis activities.";
    String projects_0_end_date "2017-03";
    String projects_0_geolocation "North Pacific Subtropical Gyre (HOT station), North Atlantic Subtropical Gyre (BATS time series station), California Margin";
    String projects_0_name "The Microbial Nitrogen Pump: Coupling 14C and Compound-specific Amino Acids to Understand the Role of Microbial Transformations in the Refractory Ocean DON Pool";
    String projects_0_project_nid "701744";
    String projects_0_start_date "2014-04";
    String publisher_name "Biological and Chemical Oceanographic Data Management Office (BCO-DMO)";
    String publisher_type "institution";
    String sourceUrl "(local files)";
    String standard_name_vocabulary "CF Standard Name Table v55";
    String subsetVariables "location";
    String summary 
"Amino acid enantiomeric ratios (D/L) of high and low molecular weight (HMW,
LMW) DOM collected from the North Pacific Subtropical Gyre and Central North
Atlantic. These data were published in Broek et al. (2019) and Broek et al.
(2017).";
    String title "Amino acid enantiomeric ratios (D/L) of high and low molecular weight (HMW, LMW) DOM collected from the North Pacific Subtropical Gyre and Central North Atlantic";
    String version "1";
    String xml_source "osprey2erddap.update_xml() v1.5";
  }
}

 

Using tabledap to Request Data and Graphs from Tabular Datasets

tabledap lets you request a data subset, a graph, or a map from a tabular dataset (for example, buoy data), via a specially formed URL. tabledap uses the OPeNDAP (external link) Data Access Protocol (DAP) (external link) and its selection constraints (external link).

The URL specifies what you want: the dataset, a description of the graph or the subset of the data, and the file type for the response.

Tabledap request URLs must be in the form
https://coastwatch.pfeg.noaa.gov/erddap/tabledap/datasetID.fileType{?query}
For example,
https://coastwatch.pfeg.noaa.gov/erddap/tabledap/pmelTaoDySst.htmlTable?longitude,latitude,time,station,wmo_platform_code,T_25&time>=2015-05-23T12:00:00Z&time<=2015-05-31T12:00:00Z
Thus, the query is often a comma-separated list of desired variable names, followed by a collection of constraints (e.g., variable<value), each preceded by '&' (which is interpreted as "AND").

For details, see the tabledap Documentation.


 
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